Field of the Invention
The present invention relates to an image processing apparatus and an image processing method, and more specifically, to a technique adapted to detect a unique portions such as a striped unevenness that may appear in an printed image by a printer.
Description of the Related Art
As this sort of a unique portion, for example, a so-called white stripe caused by ejection failure of a nozzle among multiple nozzles arrayed in a print head of an inkjet printer, or a density unevenness such as a white stripe or a black stripe caused by an error in the conveyance amount of a print medium is well known. In the past, such a unique portion in a printed image has been typically detected by visual observation by a user, or inspecting an image read by an apparatus such as a scanner.
On the other hand, Japanese Patent Laid-Open No. 2013-185862 or “‘KIZUKI’ Algorithm inspired by Peripheral Vision and Involuntary Eye Movement”, Journal of the Japan Society for Precision Engineering, Vol. 79, No. 11, 2013, which is a non-patent literature, discloses a method for detecting a unique portion from an image resulting from imaging an inspection target in accordance with a process modeling a human visual mechanism. Specifically, the first step is to divide an imaged image into a plurality of areas, and prepare a low resolution image in which luminance values of pixels included in each of the division areas are averaged. The following step is to change the phase and size of each of the division areas in the low resolution image, and obtain an addition value of averaged luminance values in each phase or for each size on a pixel basis. In doing so, when a unique portion is present in a printed image, the unique portion can be detected as a pixel having a large pixel value as compared with surrounding pixels.
However, when unique portions are periodically distributed in a printed image, the detecting method described in Japanese Patent Laid-Open No. 2013-185862 or the above-described non-patent literature sometimes cannot detect the unique portions appearing with an expected period. More specifically, depending on the relationship between the size of each division area in a direction in which the unique portions are periodically distributed and the expected period with which the unique portions are distributed, there is the possibility that the unique portions cannot be appropriately detected.